Calibration Accuracy of RCS Measurements in Free Space

When investigating Radar Cross Section (RCS) of targets, it is essential to establish confidence in the experimental calibration data. In this paper, experiments are presented which were carried out to determine the calibration accuracy achieved in performing free space target RCS measurements in the radar lab at Cranfield University. Calibration data were collected in the X-band (between 8.5 GHz and 12 GHz) using four off-the-shelf non-calibrated metallic spheres of different diameter: $\mathbf{3 0 ~ m m, ~} \mathbf{3 8}$ $\mathrm{mm}, 80 \mathrm{~mm}$ and 100 mm. The results indicate an accuracy of less than $\pm 2 \mathbf{d B m}^{2}$ for the spheres measured on a styrofoam stand and with a Signal to Noise Ratio (SNR) of at least 40 dB for all spheres.

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Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1109/metroaerospace64938.2025.11114705
Primary Topic
Human Pose and Action Recognition
Type
article
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article

Calibration Accuracy of RCS Measurements in Free Space

Human Pose and Action Recognition
article

Calibration Accuracy of RCS Measurements in Free Space

article en

Abstract

When investigating Radar Cross Section (RCS) of targets, it is essential to establish confidence in the experimental calibration data. In this paper, experiments are presented which were carried out to determine the calibration accuracy achieved in performing free space target RCS measurements in the radar lab at Cranfield University. Calibration data were collected in the X-band (between 8.5 GHz and 12 GHz) using four off-the-shelf non-calibrated metallic spheres of different diameter: $\mathbf{3 0 ~ m m, ~} \mathbf{3 8}$ $\mathrm{mm}, 80 \mathrm{~mm}$ and 100 mm. The results indicate an accuracy of less than $\pm 2 \mathbf{d B m}^{2}$ for the spheres measured on a styrofoam stand and with a Signal to Noise Ratio (SNR) of at least 40 dB for all spheres.

Defence Academy of the United Kingdom (GB)
Affordable and clean energy
Openalex Percentile: Top 45%
Human Pose and Action Recognition
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